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07/03/2023
Engression: Extrapolation for Nonlinear Regression?
Extrapolation is crucial in many statistical and machine learning applic...
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02/11/2023
Confidence and Uncertainty Assessment for Distributional Random Forests
The Distributional Random Forest (DRF) is a recently introduced Random F...
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12/09/2022
Robust detection and attribution of climate change under interventions
Fingerprints are key tools in climate change detection and attribution (...
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04/21/2022
Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions
Estimating the effects of continuous-valued interventions from observati...
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10/19/2021
fairadapt: Causal Reasoning for Fair Data Pre-processing
Machine learning algorithms are useful for various predictions tasks, bu...
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09/21/2021
PKLM: A flexible MCAR test using Classification
We develop a fully non-parametric, fast, easy-to-use, and powerful test ...
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08/02/2021
ricu: R's Interface to Intensive Care Data
Providing computational infrastructure for handling diverse intensive ca...
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07/12/2021
Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning
Despite decades of clinical research, sepsis remains a global public hea...
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06/07/2021
Proper Scoring Rules for Missing Value Imputation
Given the prevalence of missing data in modern statistical research, a b...
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05/29/2020
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression
We propose an adaptation of the Random Forest algorithm to estimate the ...
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05/12/2020
High Probability Lower Bounds for the Total Variation Distance
The statistics and machine learning communities have recently seen a gro...
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11/15/2019
Fair Data Adaptation with Quantile Preservation
Fairness of classification and regression has received much attention re...
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10/08/2019
A direct approach to detection and attribution of climate change
We present here a novel statistical learning approach for detection and ...
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08/14/2019
Causal discovery in heavy-tailed models
Causal questions are omnipresent in many scientific problems. While much...
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11/13/2018
Spectral Deconfounding and Perturbed Sparse Linear Models
Standard high-dimensional regression methods assume that the underlying ...
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11/02/2018
RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding
In this work we consider the problem of estimating a high-dimensional p ...
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01/18/2018
Anchor regression: heterogeneous data meets causality
This is a preliminary draft of "Anchor regression: heterogeneous data me...
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10/31/2017
Grouping-By-ID: Guarding Against Adversarial Domain Shifts
When training a deep network for image classification, one can broadly d...
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08/18/2017
Symmetric Rank Covariances: a Generalised Framework for Nonparametric Measures of Dependence
The need to test whether two random vectors are independent has spawned ...
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03/01/2017
Preserving Differential Privacy Between Features in Distributed Estimation
Privacy is crucial in many applications of machine learning. Legal, ethi...
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11/21/2016
Scalable Adaptive Stochastic Optimization Using Random Projections
Adaptive stochastic gradient methods such as AdaGrad have gained popular...
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10/17/2016
The xyz algorithm for fast interaction search in high-dimensional data
When performing regression on a dataset with p variables, it is often of...
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06/08/2015
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections
We present DUAL-LOCO, a communication-efficient algorithm for distribute...
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06/08/2015
backShift: Learning causal cyclic graphs from unknown shift interventions
We propose a simple method to learn linear causal cyclic models in the p...
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08/06/2013
On b-bit min-wise hashing for large-scale regression and classification with sparse data
Large-scale regression problems where both the number of variables, p, a...
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07/11/2013
Minimum Distance Estimation for Robust High-Dimensional Regression
We propose a minimum distance estimation method for robust regression in...
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03/25/2013
Random Intersection Trees
Finding interactions between variables in large and high-dimensional dat...
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10/12/2009
Node harvest
When choosing a suitable technique for regression and classification wit...
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11/13/2008
